A Steerable GA Method for Block Erection of Shipbuilding in Virtual Environment
Solving the dispatch and optimization of block erection of shipbuilding is a complex problem, especially when the spatial constraints are considered. The block erection scheduling problem can be defined as an identical parallel machine scheduling problem with precedence constraints and machine eligibility (PCME) restrictions, as well as limited layout space. An enhanced genetic algorithm (GA) is proposed to find the near-optimal solution, and a few lower bounds. Also, the percentage of the reduced makespan is defined to evaluate the performance of the proposed algorithm. The proposed GA method of steering optimization produces quicker and lesser values of makespan than the RANDOM heuristic algorithm for the collected real instances. It not only allows users to steer a computing towards effective direction and leverages computing, but also is guided by the intelligence of human to get a global view when the users are in immersive environment. The dispatch of block erection to the crane is modeled into a parallel machine scheduling problem with spatial constraints. Meanwhile a 3D layout of block erection is modeled with real size, and an interactive GA optimization is developed to solve this problem with the objective of minimizing makespan.
KeywordsSteerable Genetic algorithm Scheduling Parallel machines Shipbuilding Virtual environment
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